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Michael Snyder

Researcher at Stanford University

Publications -  938
Citations -  150929

Michael Snyder is an academic researcher from Stanford University. The author has contributed to research in topics: Gene & Genome. The author has an hindex of 169, co-authored 840 publications receiving 130225 citations. Previous affiliations of Michael Snyder include Wyss Institute for Biologically Inspired Engineering & Public Health Research Institute.

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PATH-SCAN: a reporting tool for identifying clinically actionable variants.

TL;DR: A web-based tool is developed, PATH-SCAN, which annotates individual genomes and exomes for ClinVar designated pathogenic variants found within the genes from the ACMG guidelines, which will allow individuals or researchers to identify potential risk variants in order to consult physicians or genetic counselors for further evaluation.
Journal ArticleDOI

Whole-Exome Enrichment with the Roche NimbleGen SeqCap EZ Exome Library SR Platform

TL;DR: This protocol is based on the Roche NimbleGen SeqCap EZ Exome Library SR platform, which enriches for ∼44 Mb of the human exonic regions, and can be performed at the benchside without the need for automation.
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Comprehensive whole-genome sequencing of an early-stage primary myelofibrosis patient defines low mutational burden and non-recurrent candidate genes.

TL;DR: High-coverage genome sequencing of DNA from peripheral blood granulocytes and cultured skin fibroblasts from a patient with MPL W515K-positive primary myelofibrosis found three somatic mutations of potential functional significance, consistent with that observed in similar hematopoietic tumor genomes.
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The metabolomics of human aging: Advances, challenges, and opportunities

TL;DR: The growing body of population-scale metabolomics research on aging in humans is reviewed, identifying the major trends in the field, implicated biological pathways, and how these pathways relate to health and aging.
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Metadata Checklist for the Integrated Personal Omics Study: Proteomics and Metabolomics Experiments.

TL;DR: This article is a data publication that provides the checklists for the metadata of the proteomics and metabolomics datasets of the integrative personal omics profiling study and calls for the broader use of data publications using the metadata checklist to make omics data more discoverable, interpretable, and reusable.